MDM RNA-seq Analysis Report

Author

Antoine Chaillon

Published

1 December 2025

Note

RNAseq data from Adam Fields’ Laboratory, University of California San Diego (UCSD).

Summary

  • Number of samples: 180
  • Groups: HIV- moderate cannabis, HIV- daily cannabis, HIV- naive to cannabis, HIV+ naive to cannabis, HIV+ daily cannabis, HIV+ moderate cannabis
  • Treatments: CBD, CBDpIL1B, IL1B, THC, THCpIL1B, Vehicle
  • HIV status: HIVn, HIVp
  • Cannabis use: moderate, daily, naive

Workflow Overview

We processed the RNA-seq data from monocyte-derived macrophages (MDMs) using the following pipeline:

DESeq2 Model

The differential expression model used:

\[ design(dds) ~ treatment + HIV status + cannabis \]

  • treatment: vehicle, IL1b, CBD, THC, CBD+IL1B, THC+IL1b
  • hiv_status: HIV- vs HIV+
  • cannabis: naive, moderate, daily

Summary Analyses

Volcano Plots

volcano_list[["cannabis_daily_vs_naive"]]

PCA Plots

using ntop=500 top features by variance

using ntop=500 top features by variance

using ntop=500 top features by variance

using ntop=500 top features by variance

Top Genes Tables

DT::datatable(top20_list[["cannabis_daily_vs_naive"]], options = list(pageLength = 5, scrollX = TRUE), rownames = FALSE)
Note
  • Only genes with padj < 0.05 and |log2FC| > 1 are labeled in volcano plots.
  • PCA plots can be faceted by hiv_status to observe group separation.
  • Interactive tables allow scrolling and sorting top genes for each contrast.

Pathway enrichment analysis

  • Gene Ontology (GO) enrichment analysis was performed separately for upregulated and downregulated genes for each contrast. Genes with an adjusted p-value < 0.01 and absolute log₂ fold change > 2 were selected. Enrichment analysis was conducted using the clusterProfiler package with the Biological Process (BP) ontology, using all expressed genes as the background universe. Enrichment results were visualized using dot plots, and leading-edge genes contributing to each enriched pathway were extracted for downstream interpretation.

  • Dot plots showing Gene Ontology Biological Process enrichment for upregulated (left) and downregulated (right) genes across experimental contrasts. Genes were considered differentially expressed if they exhibited an adjusted p-value < 0.01 and an absolute log₂ fold change > 2. Dot size represents the number of genes contributing to each pathway, and color indicates the adjusted p-value. Enrichment analyses were performed using the full set of expressed genes as background. Pathways are shown separately for genes increased and decreased in expression to facilitate biological interpretation.

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Top Differentially Expressed Genes

  • Heatmap showing variance-stabilized expression (VST) of the top N differentially expressed genes for the indicated contrast. Genes were selected based on adjusted p-value and absolute log2 fold change from DESeq2 analysis. Rows represent genes (labeled by gene symbol), and columns represent samples. Expression values are row-scaled (z-score) to emphasize relative expression patterns. Samples are ordered by HIV status, cannabis exposure, and treatment condition.

Selected / Candidate Genes

  • Heatmap showing variance-stabilized expression (VST) of selected genes of interest across samples. Genes were chosen a priori based on biological relevance (e.g., HIV response, inflammation, cannabinoid signaling). Rows represent genes (gene symbols), and columns represent samples. Expression values are row-scaled to highlight relative differences across conditions. Samples are ordered by HIV status, cannabis exposure, and treatment.

HIV × Cannabis Interaction Analysis in MDMs

Methods

We computed per-donor log2 fold changes (log2FC) for each treatment contrast:

\[ \text{log2FC} = \log_2(\text{Treatment} + 1) - \log_2(\text{Control} + 1) \]

Contrasts included:

  • IL1B vs Vehicle
  • CBD+IL1B vs IL1B
  • THC+IL1B vs IL1B

Known inflammatory genes were highlighted to assess whether cannabis dampens IL1β-induced inflammation. For each gene and contrast, we fitted a linear model:

Next, we extracted the interaction terms to test whether cannabis use modulates IL1β-induced inflammation.

Top HIV × Cannabis interaction genes (ordered by raw p-value)

CBD and THC Modulation of IL1β Response (Key Inflammatory Genes)

  • Grey points: all other genes — context for overall variation.
  • Colored points + labels: known inflammatory genes (IL6, TNF, CXCL10, CCL2, NFKB1).
  • Y-axis (log2FC): positive → increased by cannabinoid, negative → decreased (potential dampening).
  • Black points and error bars: mean ± SD of inflammatory genes per cannabis group and HIV status.
  • Observation:
    • Most inflammatory genes are near 0, suggesting minimal average dampening by CBD or THC.
    • Some genes show donor-specific shifts, indicating variability among donors.
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